This study aims to analyze different offline Coverage Path Planning (CPP) strategies viable for single and multiple drones that can be used in monitoring activities. The importance of this study lies in the growing demand for efficient and autonomous robotic solutions in scenarios where complete mapping and coverage of an area is crucial. Indeed, the use of offline CPP algorithms makes it possible to optimize coverage paths prior to operational execution, significantly reducing the time and energy resources required to complete assigned tasks. Nowadays, offline CPP algorithms find application in various fields including precision agriculture, surveillance, and exploration. In these scenarios, the ability to plan efficient paths without the need for human intervention during execution is of paramount importance to ensure optimal operations and minimize operational costs. After discussing the main critical issues that different algorithms must be able to handle, a classification of the different coverage strategies is provided based on their suitability for a single drone or several of them and in relation to the way the Area of Interest (AoI) is decomposed. Within each category, several algorithms extracted from the literature are then examined, whose operation is illustrated as well as their relative merits and drawbacks are described for each.
Questo studio si propone di analizzare diverse strategie di Pianificazione del Percorso di Copertura (CPP) offline valide per singolo e più droni utilizzabili in attività di monitoraggio. L'importanza di questo studio risiede nella crescente domanda di soluzioni robotiche efficienti e autonome in scenari dove la mappatura e la copertura completa di un'area sono cruciali. L'utilizzo di algoritmi CPP offline permette infatti di ottimizzare i percorsi di copertura prima dell'esecuzione operativa, riducendo significativamente il tempo e le risorse energetiche necessarie per completare i compiti assegnati. Al giorno d'oggi, gli algoritmi CPP offline trovano applicazione in vari settori tra cui l'agricoltura di precisione, la sorveglianza e l'esplorazione. In questi scenari, la capacità di pianificare percorsi efficienti senza necessità di intervento umano durante l'esecuzione è di fondamentale importanza per garantire operazioni ottimali e minimizzare i costi operativi. Dopo aver discusso le principali criticità che i diversi algoritmi devono essere in grado di gestire, viene fornita una classificazione delle diverse strategie di copertura sulla base della loro idoneità per un singolo drone o più di essi e in relazione alla modalità di scomposizione dell’Area di Interesse (AoI). All’interno di ogni categoria sono quindi esaminati diversi algoritmi estratti dalla letteratura di cui ne viene illustrato il funzionamento nonché descritti per ognuno i relativi pregi e difetti.
Investigation of suitable offline coverage path planning algorithms designed for single and multiple drones that can be deployed for monitoring purposes
Scolari, Martina
2023/2024
Abstract
This study aims to analyze different offline Coverage Path Planning (CPP) strategies viable for single and multiple drones that can be used in monitoring activities. The importance of this study lies in the growing demand for efficient and autonomous robotic solutions in scenarios where complete mapping and coverage of an area is crucial. Indeed, the use of offline CPP algorithms makes it possible to optimize coverage paths prior to operational execution, significantly reducing the time and energy resources required to complete assigned tasks. Nowadays, offline CPP algorithms find application in various fields including precision agriculture, surveillance, and exploration. In these scenarios, the ability to plan efficient paths without the need for human intervention during execution is of paramount importance to ensure optimal operations and minimize operational costs. After discussing the main critical issues that different algorithms must be able to handle, a classification of the different coverage strategies is provided based on their suitability for a single drone or several of them and in relation to the way the Area of Interest (AoI) is decomposed. Within each category, several algorithms extracted from the literature are then examined, whose operation is illustrated as well as their relative merits and drawbacks are described for each.File | Dimensione | Formato | |
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https://hdl.handle.net/10589/234139